import alphabets
name = 'models_ensemble'
log_dir = './work_dirs'
random_sample = True
keep_ratio = True
adam = False
adadelta = False
saveInterval = 1
valInterval = 10000
n_test_disp = 10
displayInterval = 5000
experiment = './expr'
alphabet = alphabets.alphabet
crnn3 = './work_dirs/pretrained_new_cont_hard_train_3_1_with_contrast_lr_0.0000080_batchSize_5_time_0316215705_/crnn_Rec_done_epoch_18.pth' 
crnn2 = './pretrained/crnn_Rec_done_epoch_7.pth'
crnn1 = './work_dirs/pretrained_new_cont_3_1_with_contrast_2_adam_lr_0.0000010_batchSize_5_time_0317110820_/crnn_Rec_done_epoch_19.pth'
beta1 =0.5
lr = 0.000001
niter = 300
nh = 256
expand_nh = 256
imgW = 10
imgH = 64
resnet_imgH = 128
batchSize = 1
workers = 2
with_crop = True
total_num = 31409
resnet_type='resnet18'
feat_size=(512, 1, 16)
